(Looking Back and Looking Forward takes a look at the articles and posts I found interesting from the previous week, along with reflections about how the trends they point to might shape my thinking about education, technology, and culture.)

At the outset of my academic career, I spent a good bit of time teaching composition courses (in English and Spanish). A cornerstone of those courses was the famed “thesis statement.”

You probably remember this one. A good thesis statement contains both the “what” and the “how/why” related to an essay.

Incomplete Thesis Statement: Internet use has a positive impact on learning.

This statement only addresses the “what” and omits the “why or “how.”

Improved Thesis Statement: The use of the Internet improves the learning experience by connecting students to additional resources and communities.

The statement now contains both a “what” — Internet usage improves the learning experience — AND the “why”/”how.”

While generative AI may be putting the survival of essay writing as a core component of the curriculum in doubt, I think the thesis statement has an important analog in the future of education: the prompt. That’s because we are moving rapidly into a world where a fundamental skill  (if not THE fundamental skill) will be the ability to instruct AI tools in the creation of narrative text, images, data, and code. And that skill requires us to teach students, from an early age, how to construct effective prompt statements.

Not surprisingly, thesis statements and generative AI prompts share a number of common elements. The most useful versions of each contain multiple parts or components. In addition, they are both designed to produce illicit responses from an audience (be it in a reader or an LLM) and the quality of those responses correlates in large part fo the context and specificity of the statement or prompt.

The similarities are such, in fact, that I think we should consider abandoning the thesis statement altogether in favor of teaching effective prompt statements. Being language/meaning based, the same people that teach the former can also learn to teach the latter. It’s simply a matter of swapping out the instructions related to what makes a “good” statement and how to identify the different components and their purpose. In the case of prompts, possible elements include:

  • Instruction: A specific task to be performed by the model.
  • Context: Additional information so that the model can respond better.
  • Input: A question that we ask the model.
  • Indicator/Response Format: Specifies the type of output.
  • Constraints or Limitations: Set any particular boundaries or limitations the system should consider while generating an output (this could be word count, number of examples, etc.)

And, unlike the case with thesis statements, where feedback generally comes in the form of correction from an instructor, prompts provide immediate results that invite exploration and iterative attempts to get the desired output. That’s right — real-time, helpful feedback and learning.

I see this evolution as both useful and positive in the learning experience. Like Maha Bali, I see generative as “technology the learner can choose to do whatever they want with – rather than technology that teachers/institutions do TO and ABOUT the learner.”

How fast will educators and our education systems adapt to generative AI? It’s hard to say. Donald Clark’s recent experience at the Learning Technologies Conference paints a good picture of the gap between educational technology’s past and future, and George Siemens provides what is likely an accurate assessment of higher education attitudes around AI (as well as what the attitudes should be).

One of the early impacts we’re already seeing is the declining value of information without application or alignment to skills and skill pathways. This past week we witnessed admissions by homework helper Chegg that ChatGPT (free) was responsible for that company declining revenue and subscriber base. That news led to an immediate drop in investor confidence related to the educational publishing giant (read information purveyor) Pearson.

Finally, with all the big tech hype around AI, it’s easy to forget that this particular “arms race” also includes plenty of open-source competitors. As one Google insider puts it, “The uncomfortable truth is, we aren’t positioned to win this arms race and neither is OpenAI. While we’ve been squabbling, a third faction has been quietly eating our lunch. I’m talking, of course, about open source.”

Further Reading

Higher Education

Cost is the biggest barrier to college enrollment

Grand Canyon University’s online enrollment tops 86,000 students, reversing declines

American faith in higher education is declining: one poll

Comparing college costs to the amount a student expects to earn after graduation

K-!2 Education

The Promise of Personalized Learning Never Delivered. Today’s AI Is Different

Workforce and Organizational Trends

IBM plans to replace 7,800 jobs with AI over time, pauses hiring certain positions

step lively

How Tech Is Transforming Entry-Level, Customer-Facing Jobs

Online Learning, Learning Design, and Education Technology

Lisa Nielsen: Embracing Post-Plagiarism: What It Means for Innovative Educators in the Age of AI

OATutor: An Open-source Adaptive Tutoring System and Curated Content Library for Learning Sciences Research

Why Is My Attitude Towards Generative AI Different From Previous AI in Education?

Donald Clark Plan B: Learning technologies 2023 – a tale of two events

Reimagining assessment practices using AI tools

SAIL: AI is the only thing

Using Neuroscience Principles to Create Powerful Cohort Learning

The Five Pathologies of EdTech Discourse About Generative AI

Instructure’s irst-quarter revenue climbs 13.6% as Canvas gains market share

Higher Education Inquirer : Cheating Giant Chegg, Shrinks 

Chegg shares drop 40% after company says ChatGPT is killing its business

Pearson shares fall after US digital learning rival says AI hurting its business

How to Design Online Classes for Higher Engagement and Retention

Technology, Science, and Culture

When will AGI arrive? Here’s what our tech lords predict

Google “We Have No Moat, And Neither Does OpenAI”

How to Label Text Data Using LLMs? 

Big Tech Jobs on the Line As Google, IBM, Dropbox Lean Into AI

Pixel Fold: Here’s Your First Official Look at Google’s New Foldable Phone

Embracing the Future: How Chatbots Can Become Great Companions

Would AIs make better professionals than humans?

Restaurant Bookings, Movie Searches Are Coming to AI-Powered Bing

This company adopted AI. Here’s what happened to its human workers

How to customize LLMs like ChatGPT with your own data and documents 

De-Dollarization: Elon Musk, Ray Dalio, Chamath Palihapitiya Weigh in